Following the success of its inaugural round of research funding, Connected Minds: Neural and Machine Systems for a Healthy, Just Society has announced the recipients of its second round of seed grants.
Led by York University, in partnership with Queen’s University, Connected Minds is the largest York-led research program, with $318.4 million in funding, in part from the Canada First Research Excellence Fund. The first-of-its-kind program brings together experts from multiple disciplines to study the risks and benefits modern technology has on society – now and in the future – with a particular focus on equity-deserving groups.
The projects receiving this round of seed grants, overseen by professors at York and Queen’s, highlight the continued dedication of Connected Minds to support pioneering interdisciplinary research that bridges technology and society, driving progress toward a more inclusive, equitable and sustainable future for all. From improving digital accessibility to developing cognitive health solutions, these projects are charting bold paths forward.
Elham Dolatabadi, assistant professor, Faculty of Health
Dolatabadi’s project, “Development and Evaluation of Multimodal Neural Models for Health Within Canada,” combines electroencephalogram (EEG) with functional magnetic resonance imaging and functional near-infrared spectroscopy in an effort to make brain-computer interface technology more affordable and accessible. The project involves collaborators from the Vector Institute – a Connected Minds partner – and the University of Toronto, focusing on inclusive health-care solutions for under-represented communities. It also emphasizes equitable data collection, model development and clinical testing, along with tailored training sessions for under-represented scholars.
Denielle Elliott, professor, Faculty of Liberal Arts & Professional Studies
In her project, “Between Alzheimer’s and War: The Struggle for Intimate and Social Memory in Yarumal, Colombia,” Elliott explores how Alzheimer’s drug innovation intersects with memory preservation in Yarumal, Colombia. This town is affected by both a hereditary form of Alzheimer’s and the legacy of armed conflict. Collaborating with experts from the Neurosciences Group of Antioquia and Medellín University, the research examines the social and historical factors influencing Alzheimer’s drug development, the impact of conflict on clinical trials and the role of hope in promoting equity. Through ethnographic methods, the project documents the experiences of Alzheimer’s-affected families while addressing health-care inequities in the Global South.
Mahtot Gebresselassie, assistant professor, Faculty of Environmental & Urban Change
Addressing the pressing accessibility barriers faced by wheelchair users, Gebresselassie leads the project “Developing an AI-Based Tool for Optimizing Disability Accessibility of Pedestrian Networks in Marginalized Neighborhoods.” Focusing on the Jane and Finch area in Toronto, the project integrates artificial intelligence (AI), aerial imagery and community insights to enhance mobility for individuals with disabilities. With expertise from Gaussian Solutions, the research aims to transform poorly maintained pedestrian networks into inclusive pathways, supporting equitable access to transportation in marginalized communities.
Keyvan Hashtrudi-Zaad, professor, Faculty of Smith Engineering at Queen’s University
Hashtrudi-Zaad leads the project “Interactive Tools for Post-Stroke Task-Oriented Upper-Limb Robotic Rehabilitation.” This research focuses on developing a home-based robotic rehabilitation system to help stroke survivors regain arm and hand functionality by practising real-life tasks such as pouring, ironing and driving. In collaboration with a researcher from Providence Care Hospital, the project integrates input from stroke survivors and therapists to ensure the system is engaging, safe and effective. It aims to increase rehabilitation access for underserved populations while addressing potential racial and ethnic differences in stroke outcomes through a diverse sample of participants.
Usman Khan, associate professor, Lassonde School of Engineering
The project “Machine Learning Integrated Quantitative Microbial Risk Assessment (ML-QMRA) for Health Risk-Based Water Treatment Optimization in Humanitarian Response” focuses on improving water safety in the Kyaka II refugee settlement in Uganda. Led by Khan, the research co-creates a machine learning tool to optimize water treatment based on microbial risk assessments. Collaborating with the Nsamizi Training Institute of Social Development, the project uses routine water quality data to reduce the risk of waterborne illnesses, particularly for vulnerable refugee populations.
Liya Ma, assistant professor, Faculty of Health
Ma leads the project “Mechanisms of Performance Monitoring: Marmoset Model.” This research investigates the neural mechanisms underlying performance monitoring, focusing on the error-related negativity (ERN), an EEG signal associated with error detection. By comparing behavioural and neural data from humans and marmosets, the project aims to identify the brain regions involved in ERN generation. In collaboration with researchers from Sunnybrook Health Sciences Centre and the Sunnybrook Research Institute – a Connected Minds partner – the research advances understanding of how the brain monitors errors and provides insights into mental health disorders. The findings also aim to support the development of reliable, wearable EEG technologies for improved diagnostics and treatment.
Ozzy Mermut, associate professor, Faculty of Science
The project “Erasing the Racism in Optical Technologies,” led by Mermut, aims to identify and eliminate racial bias in optical devices. This research evaluates how such devices respond to variations in skin melanin content, focusing on how these variations affect the accuracy of everyday and medical tools. By developing artificial tissue models and utilizing machine learning, the project will uncover potential biases in devices used by people with darker skin tones. In collaboration with the Canadian Black Scientists Network and NIRx Medical Technologies, the project seeks to establish new standards for more inclusive, ethical optical technologies, ensuring they are accurate and equitable for all users.
Laleh Seyyed-Kalantari, assistant professor, Lassonde School of Engineering
Seyyed-Kalantari leads the project “Design of Benchmarks for Fairness and Bias Evaluation and De-Biasing of Natural Language Model to Incorporate User Diversity.” This research focuses on addressing fairness issues in large language models (LLMs), like OpenAI’s ChatGPT, which often favour majority groups due to biased training data. The project aims to design domain-specific testing benchmarks to assess and score fairness across diverse dimensions such as race, gender, religion and social status. By focusing on linguistic bias, particularly in the context of sentiment analysis, the work aims to mitigate stereotypes and ensure more inclusive LLMs that better support marginalized groups, including Indigenous people, racialized communities and those with disabilities. In collaboration with the Vector Institute – a Connected Minds partner – the project seeks to advance fairness and equity in AI technologies.